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MedSeg-DFormer

A PyTorch implementation of D-Former: A U-shaped Dilated Transformer for 3D Medical Image Segmentation.

This repository hosts the codebase designed to enable high-quality segmentation of 3D medical images using a novel dilated transformer approach.

Features

U-shaped architecture with dilated transformer blocks
Optimized for medical image segmentation
Comprehensive documentation and modular code structure

Usage

Clone the repository and follow the instructions in the implementation tutorials to get started:

# Clone the repository
git clone https://github.com/transmutat/MedSeg-DFormer.git
cd MedSeg-DFormer

# Install dependencies
pip install -r requirements.txt

# Run the training
python train.py

For detailed guidance, please review /docs.

Citation

If you use this work in your research, kindly cite it:

@article{dformer,
  title={D-former: A u-shaped dilated transformer for 3d medical image segmentation},
  author={Wu, Yixuan and Liao, Kuanlun and Chen, Jintai and Wang, Jinhong and Chen, Danny Z and Gao, Honghao and Wu, Jian},
  journal={Neural Computing and Applications},
  pages={1--14},
  year={2022},
  publisher={Springer}
}